Computer networks can correspond to a number of computing devices connected via various communication links. In a typical larger scale network environment, a network may include a plurality of server and client computing devices at several geographic locations. As computer networks grow in size and complexity, there is a need for administrative tools that facilitate software distribution, asset management and/or software patch deployment. One such administrative tool is Microsoft Corporation's Systems Management Server (“SMS”).
In administrative tools, such as SMS, computers (e.g., servers) are located throughout a computer network and are configured to have a specific software distribution/management role. Often times, the specific configuration of a server will depend on the network topology and/or the anticipated software distribution load of the network. For example, in SMS, a server can have one of many possible management/distribution roles, such as a central server, distribution point, secondary site, management point, reporting point, and the like. Configuring a server device incorrectly, such as by selecting an incorrect role can result in an inefficient utilization of the server computer within the SMS system or the creation of distribution bottlenecks depending on the error. Similarly, selecting inappropriate hardware resources for a configured server (such as the number of processors, speed of processors, memory, etc.) can also result in an inefficient utilization of computer resources or the creation of distribution bottlenecks. Accordingly, capacity planning and hardware sizing functionality can become necessary for proper implementation of administrative tools.
Traditional capacity planning/hardware sizing functionality relies on static models for a network topology and server computer configuration. For example, in tools where network topology models are pre-determined, the tool does not provide adequate planning flexibility for customized network topologies. Thus, network administrators may not be able to properly model the actual configuration of the network. Additionally, the fixed static model approach does not provide adequate flexibility in facilitating various “what if” scenarios to determine the impact of different configuration settings for the server computing components in the SMS system. Accordingly, system administrators cannot typical test the impact of different server role configurations and/or hardware settings to a network model.
Thus, there is a need for a system and method for managing a distribution network that provides dynamic capacity planning and hardware sizing capabilities.